Mgr. Josef Kurka, Ph.D.
Mgr. Josef Kurka, Ph.D.
Posts:
- Department of Finance and Capital Markets
ResearcherID: ABK-4177-2022
ORCID ID: 0000-0001-8668-4308
Josef Kurka is a lecturer at IES FSV UK in Prague. His research concentrates on asset pricing, effects of various sources of risks with heterogeneous persistence, connectedness on financial markets, and time-variability of asset pricing relationships.
Job history
▷ 2025+ Lecturer, IES FSV UK, Praha
▷ 2018+ Researcher, IES FSV UK, Praha
▷ 2017+ Junior researcher, ÚTIA, Akademie věd ČR
Education
▷ 10/2025 Ph.D., IES FSV UK, Economics and finance
▷ 2014-2016 Mgr., IES FSV UK, Economics
▷ 2010-2014 Bc., IES FSV UK, Economics
Rok vydání
Monographs
Chapters in monographs
Articles
- Kurka J. (2019). Do cryptocurrencies and traditional asset classes influence each other?. Finance Research Letters, 31(December), 38-46. UT-WOS link
- Baruník J., & Kurka J. (2024). Risks of heterogeneously persistent higher moments. International Review of Financial Analysis, 96(November 2024), UT-WOS link
Contributions in the conference proceedings
JEM207 - Data Processing in Python
JEB105 - Statistics
JEM059 - Financial Econometrics I
Bachelor theses
I will be happy to consider supervising theses on any empirical economic topic, particularly focusing on financial econometrics, finance and financial markets. I will only supervise theses written in English and typeset in LaTeX.
Diploma theses
I will be happy to consider supervising theses on any empirical economic topic, particularly focusing on financial econometrics, finance and financial markets. I will only supervise theses written in English and typeset in LaTeX.
Currently supervised
1 BT, 3 DT
Grant Agency of Charles University (GAUK), Principal researcher:
▷ 2019-2022; Horizon-specific risk, higher moments, and asset prices; Grant no. 1188119
UNCE Doctoral Fellowship
▷ 2021; Extreme Volatility Risk in FX Markets
Computer skills
▷ R project, Python, Matlab
▷ Microsoft Office, VBA
Asset pricing, finance, financial econometrics, financial markets, high-frequency data, predicting sport outcomes